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Conference Paper
Real-Time Diagnosis System Using Incremental Emerging Pattern Mining
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- Authors
- Jin Hyoung Park, Heon Gyu Lee, Jong Heung Park
- Issue Date
- 2010-12
- Citation
- International Conference on Ubiquitous Information Technologies and Applications (CUTE) 2010, pp.1-5
- Language
- English
- Type
- Conference Paper
- Abstract
- Currently, as a effort to reduce a rate of death by cardiovascular diseases, a lot of researches have been studied regarding real-time diagnosis system. So, we implement a prototype which is contained of stream data processor and incremental data mining module for automatic diagnosis of cardiovascular diseases. In the prototype, (i)ECG signal data which is transported from body-attached sensor is collected and pre-processed, and (ii)diagnosis features of the bio-signal data are extracted. And the patients are automatically diagnosed using the incremental emerging pattern mining module, then (iii)the diagnosis result is provided for the doctor in charge of the patients via a web application in order to manage the medical history of each patient. So, the prototype is able to diagnose and predict patient state on real-time, automatically. ©2010 IEEE.
- KSP Keywords
- Automatic diagnosis, Cardiovascular diseases(CVD), Data mining(DM), Diagnosis system, ECG signals, Emerging pattern mining, Incremental data mining, Real-Time diagnosis, Stream Data, bio-signal, web application